3D (3-dimension) displays have recently become more and more popular, but lack of 3D content is a problem in the current market. Thus, there are methods for converting 2D image signals into 3D image signals.
FIG. 1 is a diagram illustrating a conventional 3D image generation device 10. In a conventional process of converting a 2D image into a 3D image, a depth generation device 11 is first used to estimate depth information dth from a 2D image signal 2Dv and then a depth image based rendering (DIBR) device 12 is used to generate a 3D image containing a Lv (left video) and a Rv (right video) according to the depth information dth.
The popular depth generation methods are listed as follows. (1) Video motion detection: determine a depth of an image pixel according to motion vectors (such as the techniques disclosed by U.S. Pat. No. 6,496,598). For example, when a camera makes a movement, a displacement of a near object is larger than that of a far object; therefore, a larger motion vector represents a nearer scene distance from the camera, and a smaller motion vector represents a farther scene distance from the camera. (2) Video edge characteristics detection (such as the techniques disclosed by US Publication No. 2007/0024614): determine an object boundary according to edges, and set different depth values for two boundary sides. (c) Disappeared lines and points detection: determine boundaries of a horizon or buildings according to disappeared lines and points, to thereby calculate a depth distribution of an image.